mlsanityData to 7 Oct 2026

Elastic Integrative Analysis of Randomized Trial and Real-World Data for Treatment Heterogeneity Estimation

arXiv 2005.10579 ↗First posted 21 May 2020stat.MEcited by 17

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Abstract (arXiv)

We propose a test-based elastic integrative analysis of the randomized trial and real-world data to estimate treatment effect heterogeneity with a vector of known effect modifiers. When the real-world data are not subject to bias, our approach combines the trial and real-world data for efficient estimation. Utilizing the trial design, we construct a test to decide whether or not to use real-world data. We characterize the asymptotic distribution of the test-based estimator under local alternatives. We provide a data-adaptive procedure to select the test threshold that promises the smallest mean square error and an elastic confidence interval with a good finite-sample coverage property.

Key facts. Cited by 17 papers in the map (data through 7 Oct 2026). First posted on arXiv 21 May 2020.

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Citing papers per year: 2021: 1; 2022: 1; 2023: 4; 2024: 4; 2025: 5; 2026: 2.

17 papers.

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  1. 2022Long-term Causal Inference Under Persistent Confounding via Data Combinationcited by 27
  2. 2021A Tree-based Model Averaging Approach for Personalized Treatment Effect Estimation from Heterogeneous Data Sourcescited by 14
  3. 2024Prediction-powered Generalization of Causal Inferencescited by 14
  4. 2023Falsification of Internal and External Validity in Observational Studies via Conditional Moment Restrictionscited by 10
  5. 2023Hidden yet quantifiable: A lower bound for confounding strength using randomized trialscited by 8
  6. 2025No Free Lunch: Non-Asymptotic Analysis of Prediction-Powered Inferencecited by 8
  7. 2024Adaptive-TMLE for the Average Treatment Effect based on Randomized Controlled Trial Augmented with Real-World Datacited by 7
  8. 2023Efficient and robust transfer learning of optimal individualized treatment regimes with right-censored survival datacited by 5
  9. 2024Minimax Regret Estimation for Generalizing Heterogeneous Treatment Effects with Multisite Datacited by 5
  10. 2023Comparison of Methods that Combine Multiple Randomized Trials to Estimate Heterogeneous Treatment Effectscited by 4
  11. 2024Benchmarking Observational Studies with Experimental Data under Right-Censoringcited by 4
  12. 2025Robust estimation of heterogeneous treatment effects in randomized trials leveraging external datacited by 1
5 more
  1. 2025Transportability without Graphs: A Bayesian Approach to Identifying s-Admissible Backdoor Setscited by 0
  2. 2025Rate doubly robust estimation for weighted average treatment effectscited by 0
  3. 2025Integrating RCTs, RWD, AI/ML and Statistics: Next-Generation Evidence Synthesiscited by 0
  4. 2026Testing Effect Homogeneity and Confounding in High-Dimensional Experimental and Observational Studiescited by 0
  5. 2026Bayesian fusion forests for heterogeneous treatment effects on survival from randomised and real-world datacited by 0